Full-Stack AI Engineer
Tasks
- Build AI-powered applications
- Build CI/CD pipelines
- Build ETL data pipelines
- Build RAG pipelines
- Containerize AI services
- Create frontend user interfaces
- Deploy AI and ML models
- Deploy to Kubernetes and cloud
- Develop AI inference APIs
- Develop backend services and microservices
- Ensure GDPR HIPAA SOC2 compliance
- Implement API authentication and access control
- Implement embeddings and semantic search
- Integrate LLMs with applications
- Maintain logging and observability
- Monitor model performance and cost
- Orchestrate data workflows
- Produce technical documentation
- Troubleshoot production incidents
Perks/Benefits
Skills/Tech-stack
AWS | Airflow | Azure | CI/CD | Dagster | Data labeling | Docker | ETL | Embeddings | Faiss | FastAPI | Flask | GCP | GDPR | HIPAA | Hugging Face | JavaScript | Kubeflow | Kubernetes | Logging | ML model monitoring | MLOps | MLflow | Model Monitoring | Next.js | OAuth | Observability | OpenAI | Pinecone | PostgreSQL | Prefect | PyTorch | Python | Rate Limiting | React | Retrieval-Augmented Generation | SOC2 | SQL | SageMaker | Semantic Search | TensorFlow | TypeScript | Vector Database | Vector Databases | Vertex AI | Vue | Weaviate
Education
N/A
Roles
AI Engineer | Engineer | Full Stack | Full Stack AI Engineer
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